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                "text": "Directly observable"
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        "markdown": "---\ntitle: What Can and Cannot Be Measured in AI Search | NRLC.ai\ndescription: Measurement boundaries for observed citations, mentions, Search Console data, causal attribution, and cross-engine comparisons.\norganization: Neural Command LLC\ncanonical: https://nrlc.ai/en-us/ai-search-measurement/what-can-and-cannot-be-measured/\n---\n\n← Back to measurement\n\n← Back to Measuring Visibility in AI Search\n\nMethod status: These boundaries govern the NRLC measurement convention; they do not claim access to private engine telemetry.\n\n## Directly observable\n\n- A URL or domain visibly cited in a saved answer\n- An entity named without a visible citation\n- The engine, interface, prompt, run date, and returned source list\n## Derived from a declared observation log\n\n- Under the NRLC measurement convention, citation rate = C / P. C is the number of eligible prompts with a qualifying citation; P is the total number of eligible prompts evaluated. Every reported rate must identify the engine, prompt set, denominator, and observation window.\n- NRLC defines mention rate as the share of eligible prompts where the monitored entity is named in the answer, whether or not a URL is cited. A mention without source attribution is not counted as a citation.\n- Changes between equivalent observation windows with the same scope and eligibility rules\n## Not established by GSC or one answer\n\n- ChatGPT, Claude, or Perplexity mention share\n- Causal revenue or “AI traffic” from an answer impression\n- A universal citation rate across engines with different prompt sets\n- The private retrieval path or reasoning used to produce an answer\n## Methodology for defensible claims\n\nState whether a result is directly observed, calculated from the observation log, inferred, or unavailable. Retain C and P with every citation rate, and disclose the engine, interface, prompt-set version, eligibility rules, and observation window.\n\n## Limitations\n\nThis method measures observed outputs, not private model reasoning. Results can vary by engine, interface, prompt wording, account state, and time. A citation occurrence does not prove that a source caused an answer, produced a click, or generated revenue. NRLC has not published a worked citation-rate example because there is not yet an observation log with a prompt count, engine, dates, citation count, or citation rate.\n\n## Evidence\n\nMethod\n\nNRLC AI Search Measurement method\n\nObservation window\n\nDeclared per measurement run; no aggregate run is claimed by these method pages.\n\nDataset\n\nVersioned prompt set and answer-observation log supplied by the operator\n\nMethod\n\nFreeze prompts, name the engine and interface, classify observed citation and mention outcomes, preserve exclusions, then calculate C / P over eligible prompts.\n\nAuthors\n\nJoel David Maldonado\n\nSources\n\nNRLC AI Search Measurement method, Google Search Console Performance report documentation\n\nLast verified\n\n2026-09-21\n\nConfidence\n\nfirst-party operational convention; not asserted as an industry standard\n\nLimitations\n\nObserved outputs vary by engine, interface, prompt wording, account state, and time. The method does not expose private model reasoning or establish causal attribution.\n\nView resource\n            Methodology\n\n- Performance report (Search results) — Google Search Console Help\n\n\n---\n\nSource: https://nrlc.ai/en-us/ai-search-measurement/what-can-and-cannot-be-measured/\nPublisher: Neural Command LLC\nLicense: Editorial use with attribution\n"
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